Monday, May 16, 2011

Climate Wagering - Have the Aliens Landed?

Because of a simple bet, I found a few data bases easily on line to use my own simple methods determine how fair I felt the bet to be and how confident I felt about wagering (i.e. how much I may wager myself). Since the only thing at risk is a little of my money, I can use unproven methods, make large assumptions and cherry pick the data I wish for my analysis. Should I have found the data compelling, I would have tidied up my analysis and used more standard methods to verify what is had found to justify a larger wager. The greater my confidence, the more I would bet.

So how is this different than the real world? There is no difference. A climate scientist or group of climate scientists find that there is very high risk which means a high cost to reduce the risk. The people financing the bet want to be confident enough to justify the wager, so they want more standard analysis done before writing the check. Not understanding this is odd, one might think alien behavior.

The stacked regression analysis I may have created (the same thing can be done various ways)could be considered "novel". That is a big leap, but it is just for an example. A variety of statistical analysis methods used by climate scientists are "novel". It is reasonable to me that if the climate scientist wants backers for his bet he would be willing to allow more in depth analysis of his data and methods.

This is a major sore point in the climate change debate. People expected to chip in on the financing want confirmation. The methods used by some of the scientists is novel enough that other statisticians and scientists will not sign off on the "skill" of the analysis. The reviewing statisticians and scientists need the actual codes for the analysis and data used in the analysis to reproduce the results.

For some reason, the scientists won't or can't provide the actual data and the code as used in the analysis to the reviewers. Since the reviewers can't reproduce the results, they are not willing to chip in on the wager. That's life in the high stakes climate change betting game.

Most climate scientists are human (There are a few suspected aliens, one has indicated he may be Venusian), and as all humans are fallible, make mistakes. Human scientists know that and search for their own mistakes and will grudgingly admit their mistakes should someone else find them. Alien scientists believe they are infallible, which may be true on their home world. Scientists that are alien or heavily influenced by alien cultures, don't understand the human logic of intense analysis before going all in.

Alien logic dictates that if an analysis method is less than optimum (remember they are infallible,) that increasing the complexity of the analysis improves its accuracy, though it reduces its reproducibility. The alien influence on Wall Street where Maximum Overlap Discrete Wavelet Transforms are used to determine that the longer your money is in a hedge fund the more risk you assume, illustrates the beauty of complex analysis.

Humans know that reduction in complexity is required to convince financiers to pony up the cash, if the potential financiers are wealthy, and that increasing complexity is useful in convincing the less savvy masses (pension funds), to chip in on the wager. This is the, "if you can't dazzle them with your brilliance, baffle them with bullshit" truism.

Determining if a scientist is alien or human may be a new game, "Is he/she Alien?" Any game should have reasonable rules. Perhaps we can take a test scientist for trip through the analytical gauntlet to get an idea of the basic rules.

Nicola Scafetta, is thought by a few to be of alien origin. He has a published, peer reviewed paper that used data from the ACRIM and CRU with methods outline in his paper which he suggests are clearly explained in this book. On Nicola's website he lists his publications. One of his published papers is actually written in English so that is a good one for humans to review. Note that his papers in an alien language do not necessarily prove he is an alien.

The book he referenced costs money. Savvy financiers will not invest a dime until there is a reasonable expectation of a return on that investment. So we will keep the game simple with rule number one - Shell out cash only when you expect a return on the investment.

Since we humans are on the lazy side (that is not a dig, lazy is an efficient use of mental and physical energy), Rule two - look at the easiest stuff first. The CRU data is easily download and can be imported into any spread sheet. Once on a spread sheet, we can export it to any program we wish.

The CRU data Nicola linked to is our first clue. Humans know that humans make mistakes and the more steps a human takes the more mistakes they are likely to make. The CRU data has no notes. Those may be on a previous page, but the link was to a page that had no notes. The data on that page appears to be monthly temperatures with annual averages below in the next row. Mixing data by rows complicates the use of the data. Also the data appears to be space separated values, but the number of spaces are inconsistent for the apparent monthly data further complicating the use of the data. There are 13 columns in the apparent monthly data. One of those columns may be a monthly average or they number of months may be based on an alien calendar. A quick check indicates the 13th column is likely to be an average of the monthly temperature anomaly. The data that appeared in the alternate rows then may be actual temperature rather than anomaly. Since I don't care, I am trashing the alternating rows and just using what appears to be anomaly data. I would assume the anomaly data is global average anomaly, but since I am human and therefore lazy, I am not going to waste my time trying to find out for sure. It is my money Nicola wants, if he wants it bad enough he will make it easier for me to justify the investment. I expended the least amount of effort possible to organize the data he linked for my analysis.

If I didn't mess up, this may be the data that Nicola used. If I did mess up, I don't really care. I am not selling this stuff, Nicola is, I just want to see if it is worth the investment.

The ACRIM data is somewhere on the page Nicola linked. Right now I am pretty sure that Nicola is not a very good salesman. The more work I have to do, the less likely I will invest. If Nicola was really hungry to sell, he would simplify the effort for potential buyers. Since I just happen to have the ACRIM TSI data and a few other TSI records/reconstructions from Leif Svalgard's website, I will use them instead of fighting with ACRIM site which lists data products but won't let me down load them.

The solar TSI data has a mean of roughly 1366. I adjusted the DORA set so that it has the same mean value for the same range (I trimmed the Hadcru set a few years so I am using the same time periods for the DORA set.) Since the ARCIM set is short, I adjusted its mean, but let it float a little above the mean of the others. Both TSI sets were scaled with 0.25 multiplier to roughly match the amplitude of the temperature set.

Above is a chart with the data collected. Scaling can be changed as needed based on Nicola's paper to see what it looks like. I used the DORA TSI set because I want something recent and unbiased. If need be, I can add the Lean at al 2000 or Lean et al 1995, but since both have been revised, I would rather avoid their use.

In Nicola's abstract, he states that they find that at least 60% of the warming since 1970 is due to natural effects created by the orbital cycles of planets, mainly Jupiter and Saturn. The planet's gravitational forces tend to tug the Sun around, changing its impact on climate. This impact is seen in decadal and bi decadal cycles. In the introduction Nicola lists a variety of oscillations that appear to some what match the orbital cycles and even mentions the Chinese calendar which most of us have seen parts of while enjoying Chinese buffets. A pretty convincing argument that there is a lot of stuff going on, but I will pause momentarily to order Chinese.

Before spending much time trying to reproduce his work, I would like to see if it is worth the effort. Nicola's paper was accepted in April of 2010. The most recent TSI reconstruction he listed was Solanki 2007 with Lean 2005, 2000 and 1995 and Hoyt 1997. Without creative methods, there is not much correlation between the HADCRU temperature series and the TSI measurement (ACRIM) and reconstruction (DORA.)

The Solanki 2007 is not on this chart using Svalgard's data. The Wang reconstruction should be the same or similar to the Lean 2005. It would appear that since the TSI reconstructions Nicola used are a little out dated that his conclusions may be over estimated. This causes this potential investor to think:

1. The newer data will likely change the results.

2. Since the code for Nicola's paper is not available, I would have to reinvent the wheel to first replicate his code, then update the data used in his analysis to see if newer TSI reconstructions changed the results.

Conclusion: Nicola probably is not an alien because he exhibits the human trait of laziness by not providing working code and as used data sets. However, the complexity of his analysis does tend to lean toward alien behavior. This possible investment will be tabled until the proposal is revised. Time to eat Chinese.

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